Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Multi-Feature Hierarchical Template Matching Using Distance Transforms
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
A Mixed-State Condensation Tracker with Automatic Model-Switching
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
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In this paper, we depict a novel approach to improve the moving object tracking system with particle filter using shape similarity and color histogram matching by a new integrated framework. The shape similarity between a template and estimated regions in the video sequences can be measured by their normalized cross-correlation of distance transformation image map. Observation model of the particle filter is based on shape from distance transformed edge features with concurrent effect of color information. The target object to be tracked forms the reference color window and its histogram are calculated, which is used to compute the histogram distance while performing a deterministic search for matching window. For both shape and color matching reference template window is created instantly by selecting any object in a video scene and updated in every frame. Experimental results have been offered to show the effectiveness of the proposed method.